DocumentCode
902941
Title
Threading and autodocumenting news videos: a promising solution to rapidly browse news topics
Author
Wu, Xiao ; Ngo, Chong-Wah ; Li, Qing
Volume
23
Issue
2
fYear
2006
fDate
3/1/2006 12:00:00 AM
Firstpage
59
Lastpage
68
Abstract
This paper describes the techniques in threading and autodocumenting news stories according to topic themes. Initially, we perform story clustering by exploiting the duality between stories and textual-visual concepts through a co-clustering algorithm. The dependency among stories of a topic is tracked by exploring the textual-visual novelty and redundancy of stories. A novel topic structure that chains the dependencies of stories is then presented to facilitate the fast navigation of the news topic. By pruning the peripheral and redundant news stories in the topic structure, a main thread is extracted for autodocumentary
Keywords
content-based retrieval; information analysis; video retrieval; autodocumentary extraction; coclustering algorithm; news video autodocumentation; textual-visual concepts; Assembly; Cellular neural networks; Clustering algorithms; Data mining; Documentation; Fuses; Navigation; Signal processing algorithms; Videos; Yarn;
fLanguage
English
Journal_Title
Signal Processing Magazine, IEEE
Publisher
ieee
ISSN
1053-5888
Type
jour
DOI
10.1109/MSP.2006.1621449
Filename
1621449
Link To Document